Security News > 2021 > April > Scientists develop quantum machine learning methods for reasoning

Scientists at Cambridge Quantum Computing have developed methods and demonstrated that quantum machines can learn to infer hidden information from very general probabilistic reasoning models.

The proofs of principle suggest quantum machines using highly expressive inference models could enable new applications in diverse fields.

The paper draws on the fact that sampling from complex distributions is considered among the most promising ways towards a quantum advantage in machine learning with today's noisy quantum devices.

This pioneering work indicates how quantum computing, even in its current early stage, is an effective tool for studying science's most ambitious questions such as the emulation of human reasoning.

Machine learning scientists across industries and quantum software and hardware developers are the groups of researchers that should benefit the most from this development in the near-term.

With quantum devices set to improve in the coming years, this research lays the groundwork for quantum computing to be applied to probabilistic reasoning and its direct application in engineering and business-relevant problems.

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